In this paper, we first frame the use of artificial intelligence (AI) systems in the public sector as a continuation and intensification of long-standing rationalization and bureaucratization processes. Drawing on Weber, we understand the core of these processes to be the replacement of traditions with instrumental rationality, that is, the most calculable and efficient way of achieving any given policy objective. Second, we demonstrate how much of the criticisms, both among the public and in scholarship, directed towards AI systems spring from well-known tensions at the heart of Weberian rationalization. To illustrate this point, we introduce a thought experiment whereby AI systems are used to optimize tax policy to advance a specific normative end: reducing economic inequality. Our analysis shows that building a machine-like tax system that promotes social and economic equality is possible. However, our analysis also highlights that AI-driven policy optimization (i) comes at the exclusion of other competing political values, (ii) overrides citizens’ sense of their (non-instrumental) obligations to each other, and (iii) undermines the notion of humans as self-determining beings. Third, we observe that contemporary scholarship and advocacy directed towards ensuring that AI systems are legal, ethical, and safe build on and reinforce central assumptions that underpin the process of rationalization, including the modern idea that science can sweep away oppressive systems and replace them with a rule of reason that would rescue humans from moral injustices. That is overly optimistic: science can only provide the means – it cannot dictate the ends. Nonetheless, the use of AI in the public sector can also benefit the institutions and processes of liberal democracies. Most importantly, AI-driven policy optimization demands that normative ends are made explicit and formalized, thereby subjecting them to public scrutiny, deliberation, and debate.

中文翻译：

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人工智能、合理化和公共部门的控制限制：税收政策优化案例

在本文中，我们首先将人工智能（AI）系统在公共部门的使用视为长期合理化和官僚化进程的延续和强化。借鉴韦伯的经验，我们理解这些过程的核心是用工具理性取代传统，即实现任何给定政策目标的最可计算和最有效的方式。其次，我们展示了公众和学术界对人工智能系统的批评有多少源自韦伯理性化核心的众所周知的紧张局势。为了说明这一点，我们引入了一个思想实验，利用人工智能系统来优化税收政策，以推进特定的规范目标：减少经济不平等。我们的分析表明，建立一个促进社会和经济平等的机器般的税收制度是可能的。然而，我们的分析还强调，人工智能驱动的政策优化（i）排除了其他相互竞争的政治价值观，（ii）超越了公民对彼此的（非工具性）义务的感觉，以及（iii）破坏了人类作为自我决定的存在的观念。第三，我们观察到，旨在确保人工智能系统合法、道德和安全的当代学术和倡导建立在并强化了支撑理性化过程的中心假设之上，包括科学可以扫除压迫性系统并用新的系统取代它们的现代观念。一条将人类从道德不公正中拯救出来的理性规则。这过于乐观了：科学只能提供手段，而不能决定结果。尽管如此，人工智能在公共部门的使用也有利于自由民主国家的机构和进程。最重要的是，人工智能驱动的政策优化要求规范目标明确和正式，从而使它们受到公众的监督、审议和辩论。